We propose to develop statistical methods for the analysis of longitudinal magnetic reso- nance imaging (MRI) data for patients with multiple sclerosis (MS). Disease biomarkers identi?ed from MRI are necessary for studying disease progression in observational studies and for assessing treatment effects of therapies in clinical trials. We propose statistical methods for the analysis of longitudinal MRI intensity time courses that integrate information across multiple modalities. The proposed methods will harness the complex data structure of clinical MRI for identifying biomarkers that can be utilized in future studies and that are implementable in MS centers across the country.